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In modern economic literature, the most common measure of a taxpayer's loss from a distortionary tax, such as a tax on bicycles, is the equivalent variation, the maximum amount that a taxpayer would be willing to forgo in a lump sum to avoid the tax. The deadweight loss can then be interpreted as the difference between the equivalent variation ...
Data envelopment analysis (DEA) is a nonparametric method in operations research and economics for the estimation of production frontiers. [1] DEA has been applied in a large range of fields including international banking, economic sustainability, police department operations, and logistical applications [2] [3] [4] Additionally, DEA has been used to assess the performance of natural language ...
A chained volume series is a series of economic data (such as GDP, GNP or similar kinds of data) from successive years, put in real (or constant, i.e. inflation- and deflation-adjusted) terms by computing the aggregate value of the measure (e.g. GDP or GNP) for each year using the prices of the preceding year, and then 'chain linking' the data together to obtain a time-series of figures from ...
In an economic model, an exogenous variable is one whose measure is determined outside the model and is imposed on the model, and an exogenous change is a change in an exogenous variable. [1]: p. 8 [2]: p. 202 [3]: p. 8 In contrast, an endogenous variable is a variable whose measure is determined by the model. An endogenous change is a change ...
Free add-on to STATA to compute inequality and poverty measures; Free Online Software (Calculator) computes the Gini Coefficient, plots the Lorenz curve, and computes many other measures of concentration for any dataset; Free Calculator: Online and downloadable scripts (Python and Lua) for Atkinson, Gini, and Hoover inequalities
The dynamic lot-size model in inventory theory, is a generalization of the economic order quantity model that takes into account that demand for the product varies over time. The model was introduced by Harvey M. Wagner and Thomson M. Whitin in 1958.
Data valuation is a discipline in the fields of accounting and information economics. [1] It is concerned with methods to calculate the value of data collected, stored, analyzed and traded by organizations. This valuation depends on the type, reliability and field of data.
because these are simply the most common patterns found in the data. A simple review of the above table should make these rules obvious. The support for Rule 1 is 3/7 because that is the number of items in the dataset in which the antecedent is A and the consequent 0. The support for Rule 2 is 2/7 because two of the seven records meet the ...